About us

The team MABioVis develops a scientific vision inspired by the synergy now
taking place between information sciences, life sciences, social sciences and
economics. The combination of experimental techniques for high-speed and advanced
computational methods allows to tackle problems of unprecedented size, and gives
birth to scientific issues emerging in a variety of fields such as biology and
quantitative geography.

In the different areas that we study, the data can be modeled by complex systems
defined as sets of interacting entities. Members of the MABioVis team contribute to
the development and study of formalisms, models and algorithms providing results
on both extraction and data management, but also on the construction, analysis and
understanding of these complex systems. The results obtained and the ties with academic
and industrial partners show that we have been successful at addressing this challenge
in biology (life systems) and quantitative geography (urban networks).

Several members of our group are also a part of the PLEIADE and
MNEMOSYNE projects from INRIA.
Some members of our group are involved in the management of the Bordeaux
Bioinformatics Center - CBiB (within the Bordeaux Functional Genomics Center)
which is an ISO 9001 certified core facility. It provides access to biological data analysis and programming
expertise as well as access to high-performance computing resources for wet labs. The resources serve scientists
and private labs to master the bioinformatics needs of their research in an efficient and cost-effective manner.
CBiB is recognized at the national and international levels as member of
French Bioinformatics Institute (IFB).

Publications

Themes

CoBalt

- Computational Biology

The research conducted in CoBalt takes its source in many areas in biology or bio-informatics and from biological
data: genomic and protein sequences, RNA, biological interaction networks, metabolic and signaling pathways. We aim at
the development of new algorithms and formal models for the analysis of genomes, networks, and more generally the study
of complex systems. We ultimately support biologists in their understanding of the structure and the history of
genomes. We thus address challenges initiated from problems in bioinformatics while encompassing issues in computer
science: algorithmic recognition and inference patterns, data mining and classification, modeling of complex dynamical
systems, prediction and comparison of networks, comparative genomics in a broad sense. Full details

EVADoMe

- Visual Analytics & Interactive Exploration of Massive Data

The research conducted in EVADoMe is based on three main lines of research: data mining, graph drawing and visual
interactive exploration of data. Data mining can be viewed as an upstream process for visual data analysis.
Graph drawing consists in emebedding the vertices of a graph in a geometrical space (a 2D Euclidean space is commonly
used in information visualization). When designing a visualization system, often starting from user tasks and
available data, one must decide of a proper visual representation coupled with task-relevant interactions. We have
investigated the use of GPU’s to improve interactivity when exploring sophisticated graph drawing for large graphs
(typically using curves for edges). Full details